AI-Driven Personalization in Inflight Catering: From Passenger Profiles to Plate

Abstract

The incorporation of intelligent systems into aircraft meal service marks a notable evolution in flying experiences. By utilizing complex information frameworks that link traveler preferences with eating behaviors, airlines now provide customized dining options while simultaneously enhancing supply chain efficiency. Four distinct algorithmic approaches—collaborative filtering mechanisms, passenger segmentation frameworks, iterative reinforcement protocols, and neural network implementations—establish feedback systems of increasing accuracy. These systems operate through modern technical infrastructure, including API gateways, event-driven messaging, microservices, containerization, and service mesh architectures that ensure scalability and resilience. Careful merging of advanced computing systems with everyday flight operations allows airlines to better predict food needs, manage supplies effectively, and deliver superior meal service. The changes do more than just make travelers happier - they bring real business improvements: kitchens spend less on ingredients, planes burn less fuel by carrying lighter loads, crew members work more efficiently, and fewer leftovers end up in landfills, helping protect our planet. The resultant paradigm constitutes a fundamental reconfiguration of culinary service methodology within commercial aviation contexts.